PPI Darren Gitelman

8/9/2019 PPI Darren Gitelman

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DarrenGitelman,

MD

[email protected]


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D.GitelmanD.Gitelman

Functionalintegration Analysesofinterregionaleffects

Whataretheinteractionsbetween

theelementsofaneuronal

system?

Univariate&Multivariateanalysis

Functionalintegration Analysesofinterregionaleffects

Whataretheinteractionsbetween

theelementsofaneuronal

system?

Univariate&Multivariateanalysis

Functionalspecialization Analysesofregionallyspecific

effects

Whichregionsarespecializedforaparticulartask?)

Univariateanalysis

Functionalspecialization Analysesofregionallyspecific

effects

Whichregionsarespecializedforaparticulartask?)

Univariateanalysis

K.Stephan,FIL

StandardSPM

Effectiveconnectivity

Effectiveconnectivity

Functionalconnectivity

Functionalconnectivity


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Functionalintegration

Functionalintegration

Functionalconnectivity Temporalcorrelationsbetween

spatiallyremote

areas

MODEL-FREE

Exploratory

Data Driven

No Causation

Whole brain connectivity

Functionalconnectivity Temporalcorrelationsbetween

spatiallyremote

areas

MODEL-FREE

Exploratory

Data Driven

No Causation

Whole brain connectivity

Effectiveconnectivity Theinfluencethatoneneuronal

systemexerts

over

another

MODEL-DEPENDENT

Confirmatory

Hypothesis driven

Causal (based on a model)

Reduced set of regions

Effectiveconnectivity Theinfluencethatoneneuronal

systemexerts

over

another

MODEL-DEPENDENT

Confirmatory

Hypothesis driven

Causal (based on a model)

Reduced set of regions

K.Stephan,FIL;S.WhitfieldGabrieli

PPI


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maineffect

oftask

maineffect

ofstim.

type interaction

Confounds

+ error

Task factorTask A Task B

TA/S1 TB/

S1

TA/S2 TB/S2

Stim1

Stim2

Stimulusfa

ctor

y

y


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T

S

A B

SignificantInteraction

(TxS)

Factor Tissignificant

FactorSissignificant

FactorsT&Saresignificant

Significant

maineffectsandinteraction

NomaineffectNointeraction

A BT

A BT

A BT

A BT

A BT


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Two

(or

more)

experimental

/

psychological

factors

Changein

regression

slope

due

to

the

differentialresponsetooneexperimentalcondition undertheinfluenceofdifferent

experimentalcontexts.


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Task:Lettersandtonespresented

simultaneously.(PET

scan).

Factor1:Tonespresentedatdifferentrates.

Factor2:Subjectsattendandrespond toeithera

targetletter

(A)

or

atarget

tone

(low)

.

Is

there

a

differential

sensitivity

to

the

presentationrateoftoneswhenpayingattentiontotonesvs.payingattentiontoletters?

Frith&Friston,Neuroimage,1996


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Attention (A)Tones Letters

)

AT/R1 AL/R1

AT/R2 AL/R2

Stim

1

Stim2

Pres

entation

rate(R)

AT/R3 AL/R3Stim3

Tonesvs.Letters

Rateoftones

interaction



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Activityinauditorycortexvariesbypresentationrateregardlessof

whethersubjectspaidattentiontotonesorletters.



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Activityintherightthalamusisinfluencedbypresentationrateoftoneswhensubjectsattendedtotonesvs.attendingtoletters.



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Two(or

more)

physiological

factors

(i.e.,

neural

activitysignals)

Changeinregressionslopeduetothedifferentialresponseofthesignal(neuralactivity)from

region1due

to

the

signal

from

region

2.


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D.Gitelman Bucheletal,CerebCortex,1997

Key

M=Dummyscans(discarded)

F=

Fixation(central

dot)

A=Attention:radiallymoving

dots.Subjectstoldtodetect

changesinspeedofdots(no

changesactually

occurred

duringscanning).

N=Noattention:radiallymovingdotsviewedpassively.

S=Stationary:250stationary

dots


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Task factor

Attention No attention

TA/S1 TN/S1

TA/S2 TN/S2

Nomotion

Motion

Stim

ulusfactor

SM

NA

SS

TT )(

SM

NA

SS

TT )(

Region1 Region2 interaction

ActivityinRegion1

ActivityinRegion2


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Task:Subjectsaskedtodetectspeedchangesinradiallymovingdots(fMRI).

Doesactivityinposteriorparietal (PP)cortex

(attentional

area)

modulate

the

response

to

V1

(motionarea)activity(oristhereacontributionfromPPthatdependsonV1activity)?

Fristonetal,Neuroimage,1997

Region1 Region2 interaction


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D.GitelmanD.Gitelman Fristonetal,Neuroimage,1997

modulationoftheV1V5contributionbyPP? modulationofthePPV5contributionbyV1?

Z=5.77

P


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1Physiologicalfactor(neuralactivity)

1Psychologicalfactor(experimentalcontext)

Change

in

regression

slope

due

to

the

differential

responseofthe signalfromoneregionundertheinfluenceofdifferentexperimentalcontexts.

Bilinear

model

of

how

the

psychological

contextchangestheinfluenceofoneareaonanother.

Friston et al. NeuroImage, 1997


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Task factor

Attention No attention

TA/S1 TN/S1

TA/S2 TN/S2

Nomotion

Motion

Stim

ulusfactor

SM

NA

SS

TTT )(

SM

NA

SS

TTT )(

Taskfactor SourceRegion

interaction

Psychologicalfactor

ActivityinSourceregion


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D.GitelmanD.Gitelman Fristonetal,Neuroimage,1997

Task:Subjectsaskedtodetectspeedchangesinradiallymovingdots(fMRI).

Doesthetask(attention)modulatetheresponse,

to

V1

activity,

or

does

activity

in

V1

influence

the

responsetoattention?[Inferenceontaskandregionaleffects]

Taskfactor SourceRegion

interaction


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Twopossibleinterpretations Modulation

of

the

contribution

of

V1

to

V5

by

attention

(context

specific) ModulationofattentionspecificresponsesinV5byV1inputs

(stimulusspecific)



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Activityinregion

k

Experimentalfactor

Responseinregioni

=k+ T + kx T

k T

+ kx T

Activityin

regionk

Experimental

factor

Responseinregioni

=k+ T + kx T

k T

+ kx T

Contextspecificmodulationofresponsestostimulus

Stimulusrelatedmodulation ofresponsestocontext(attention)



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ArePPIs

the

same

as

correlations?

No

PPIsarebasedonregressionsandexplicitly

discountmain

effects (discountsimplecorrelations)


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KimandHorwitzinvestigatedcorrelationsvs.PPIregression

using

abiologically

plausible

neural

model.

PPI

results

were

similar

to

those

based

on

integratedsynapticactivity(goldstandard)

Resultsfromcorrelationswerenotsignificantfor

manyof

the

functional

connections.

Achangeininfluencebetween2regionsmaynot

involveachangeinsignalcorrelation

Kim&Horwitz,MagResMed,2008


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AlthoughPPIsselectasourceandfindtargetregions,theycannotdeterminethedirectionality

ofconnectivity.

Theregressionequationsarereversible.TheslopeofA BisapproximatelythereciprocalofBA

(notexactly

the

reciprocal

because

of

measurement

error)

Directionalityshouldbeprespecifiedandbasedonknowledgeofanatomyorotherexperimental

results.

Source Target Source Target

?


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Becausetheyconsistofonly1inputregion,PPIsare

modelsof

contributions

rather

than

effective

connectivity.

PPIsdependonfactorialdesigns,otherwisetheinteractionandmaineffectsmaynotbeorthogonal,and

the

sensitivity

to

the

interaction

effect

will

be

low.

ProblemswithPPIs

Interactionterm

not

formed

correctly

(as

originally

proposed)

Analysiscanbeoverlysensitivetothechoiceofregion.


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V1xAttention

Psychophysiological

interaction

term

originally

formed

by

multiplyingmeasureBOLDsignalbycontextvector(orby

anotherBOLDsignalinthecaseofphysiophysiologicalinteractions)

Friston,etal.Neuroimage,1997

xkx gp


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Regionalactivity

measured

as

aBOLD

time

series

=hemodynamicresponse neuralactivity

=convolution

InitialformulationofPPIestimatedtheinteractionterm

as

BOLD

xcontext

vector.

BUT:Interactionsactuallyoccurataneuronallevel! Thereforeneuronalactivitymustbeestimatedfrom

hemodynamicactivity

But,thisisdifficultbecausemappingfromBOLDsignaltoneuralsignalisnonunique(duetolossofhighfrequencyinformation)(Zarahn,Neuroimage,2000)


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Hxyxhytt

yt =MeasuredBOLDsignalh=hemodynamic (impulse)responsefunctionxt =neuronalsignal

H =HRF

in

Toeplitz

matrix

form

Gitelmanetal.,Neuroimage,2003

BABABA

xxHHxHxyy

AAA PxHHxHPHPy


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D.GitelmanD.Gitelman Gitelmanetal.,Neuroimage,2003

HRF HRF


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HRF


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Cantryusingamaximumlikelihoodestimator(i.e.,

leastsquares)

but

this

runs

into

trouble

with

high

frequencycomponents. Zarahnconstrainedtheestimatestoparticulartemporal

intervals.(Zarahn,Neuroimage,2000)

CantryusingaWeinerfilter,butthisrequireshighSNRandanestimateofthenoisespectraldensity.(Glover,Neuroimage,1999)

Useempirical

Bayes

deconvolution

to

finesse

the

noiseestimatesbysettingthepriorprecisionsonthehighfrequenciesto0.(Gitelman,Neuroimage,2003)

Gitelmanetal.,Neuroimage,2003


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BOLD

Neural


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D.Gitelman


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D.Gitelman

Istheredletterleftorrightfromthemidlineoftheword?

group analysis (random effects),

n=16, pletterdecisions

Stephan et al, Science, 2003


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Bilateral ACC activation in both tasks

but asymmetric connectivity !

IPS

IFG

Left ACC left inf.frontalgyrus(IFG):increaseduringletter decisions.

Right ACC right IPS:

increase

during

spatial decisions.

leftACC(6,16,42)

rightACC(8,16,48)

spatialvs.letterdecisions

lettervs.spatial

decisions

groupanalysisrandomeffects(n=15)

p


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PPI single-subject example

bVS=0.16

bL=0.63

Signal

in

left

ACC

Sign

alin

leftIFG

bL=0.19

Signal

inright

ant.

IP

S

Signal

in

right

ACC

bVS=0.50

LeftACCsignalplottedagainstleftIFG

spatial

decisions

letterdecisions

letterdecisions

spatialdecisions

RightACCsignalplottedagainstrightIPS

Stephan et al, Science, 2003


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D.GitelmanD.Gitelman Veldhuizenetal., ChemSenses,2007


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D.GitelmanD.Gitelman Veldhuizenetal., ChemSenses,2007


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D.GitelmanD.Gitelman Veldhuizenetal.,OHBM2009

Atalowerthreshold(Punc =0.005,influences

wereseenfromFEF,POandPPConAI/FO.


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D.GitelmanD.GitelmanVeldhuizenetal.,OHBM2009


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Inkblottest

Common/frequent Infrequent

Rare/unusual

Increased

in

schizophrenia

and

certain

personality

disorders

Associatedwithunusualperceptionandhigherpercentageofunusualresponsesinartisticpopulations.

Sinceamygdala

activity

can

affect

perceptual

processinghypothesisisthatamygdalaisactiveduringinkblottest.

http://www.testderorschach.com.ar/en/inkblots.htmAsari

et

al.,

Psych

Res,

2010


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VBMdemonstratedincreasedamygdala&cingulatevolumeinsubjectswithmoreunusualresponses.

Asarietal.,Cortex,2010


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fMRIstudyresponsestoinkblottest [unique frequent]:temporalpole (p


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Temporalpolemaylinksensoryinputfromoccipitotemporal

regionswithtopdownfrontalcontrolandemotional

modulationbytheamygdalaAsarietal.,Neuroimage,2010


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Saccade

Explore

Central


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Areasshowingconnectivitywiththesuperiorcolliculusundertheexplore

butnot

the

saccade

condition


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Pros:

Givenasingle

source

region,

we

can

test

for

its

context

dependentconnectivityacrosstheentirebrain

Simpletoperform

Cons: Very

simplistic

model:

only

allows

modelling

contributions

fromasinglearea

Ignorestimeseriespropertiesofdata(candoPPIsonPET

and

fMRI

data) Inputsarenotmodelledexplicitly

Interactionsareinstantaneous

K.Stephan,FIL


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NonfactorialPPIsareinefficient PPI termandP(psychologicalvariable)arehighlycorrelated (0.86)in

thematrix

shown

below.

This

will

reduce

the

sensitivity

for

estimating

thePPIeffect(basedonattentiontomotiondataset)

Tableof

correlations

between

regressors


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Seethe

paper:

McLaren,

D.G.,

Ries,

M.L.,

Xu,

G.,

Johnson,S.C.,2012.Ageneralizedformofcontextdependentpsychophysiological

interactions(gPPI):

acomparison

to

standard

approaches.NeuroImage61,12771286.

NITRC.ORGsite:

https://www.nitrc.org/projects/gppi


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Psychological

regressor

Regionalsignal

PPI

D.McLaren,Neuroimage,2012


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SPMPPI SPMPPI2

conditions

gPPI

A[fix](1condition) .9876 .9876

AB(2conditions) .8675 .9889

SPMPPI1

condition

SPMPPI2

conditions

gPPI

A[fix](1condition) 3.6676 3.6676

AB(2conditions) 6.4581 3.5447

BetaEstimates

SumsofSquares

D.McLaren,personalcommunication


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D.GitelmanD.Gitelman D.

McLaren,

Neuroimage,

2012


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McLaren,

Neuroimage,

2012

k

=

#

regressorsn=#timepoints

RSS=residual

sumofsquares


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PlotofAIC:Lowerisbetter

D.McLaren,

Neuroimage,

2012


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McLaren,

Neuroimage,

2012


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IncludingmaineffectsinmyPPIanalysistakes

awayall

the

interaction

results.

Do

Ihave

to

includemaineffects?

Absolutely!Otherwise,theinferenceoninteractions

willbe

confounded

by

main

effects.

ShouldIincludemovementregressorsinmyPPIanalysis?

Yes,include

any

nuisance

effects

you

would

normally

include.


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Whatdoes

it

mean

to

adjust

for

different

effects?

Adjustingforeffectsmeanskeepingeffectsofinterest

andremovingeffectsofnointerest,e.g.,movement

regressors,block

effects,

etc.

InordertoadjustaneffectsofinterestFcontrast

shouldbesetupbeforetryingtoextractthedata.


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ShouldVOIsbebasedontheexactlocationsof

groupeffects

or

should

they

be

subject

specific?

Both.VOIsshouldbesubjectspecific,butshouldbe

closeenoughto amaximabasedonagroup

analysis,

the

literature

,

etc.

Close

enough

depends

onwherethemaximaisinthebrain,thesmoothnessofthedata,etc.Closeenoughinthecaudatemightbe5mm,whileintheparietalcortex,close enough

mightbe

1cm.


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HowdoIselectregionsthatarecloseenoughtoamaxima? Displayacontrastthatshowstheregionsofinterest. MovetheSPMcursortothegroupmaxima. Rightclickinthegraphicswindownexttotheglassbrain.The

cursorwilljumptotheclosestmaxima,andthenumberofmmit

moveswill

be

recorded

in

the

Matlab

window.

Make

anote

of

howfarthecursormoves. Nowclickeigenvariateandextractasusual

HowbigshouldtheVOIsbe?

Thisdepends

on

the

smoothness

of

the

data

and

the

region.

If

youhavehighresolutiondata orareinasubcorticalnucleusyouprobablywantasmallersphere.Generallybetween4and8mmradiusspheresareused.


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Howis

agroup

PPI

analysis

done?

Theconimagesfromtheinteractiontermcanbebroughttoastandardsecondlevelanalysis(onesamplettestwithinagroup,twosamplettest

betweengroups,

ANOVAs,

etc.)

CanIrunaPPIbasedonasinglemaineffect? Yes,butthisisnotanoptimaldesign.Itisimportantto

realizethat

the

interaction

term

will

be

very

highly

correlatedwiththemaineffectregressor,resultinginverylowpowerfordetectingtheinteractioneffect.


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RunastandardGLManalysis Includeconditionsandanynuisanceeffects(motion,etc.)

Foreaseofanalysiscombinemultiplesessionsintoasinglesessionandincludeblockeffects

Displaycontrastofinterest

ExtractVOI

(volume

of

interest),

adjusting

for

effectsofinterest(i.e.,excludeanynuisanceregressors)

PPIbutton

(makes

PPI

regressors)

SPM.matfilefromstandardGLManalysis

SetupcontrastofPsychconditions


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RunPPIGLManalysis

PPI.ppi(interaction)

PPI.Y(maineffect:sourceregionBOLDdata)

PPI.P

(main

effect:

Psych

conditions

that

formed

PPI) Contrastis[100]forpositiveeffectof

interactionand[100]fornegativeeffect

(assumingconditions

entered

in

order

listed)


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Theanalysis

directory

should

include:

Directorynamedfunctionalwhichincludesthe

preprocessedfMRIvolumes

Directoryname

structural,

which

includes

aT1

image

Files:factors.mat,block_regressors.mat,

multi_condition.matandmulti_block_regressors.mat

Make3empty

directories

called

GLM,

PPI

V2

and

PPIV5


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FromMatlab

command

prompt

>>cdpathtoanalysisdirectory

MakesureSPM12isintheMatlabpath

Start

SPM:

spm

FromtheTasksmenuatthetopoftheGraphics

windowchoose

Batch


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D.Gitelman

FromtheSPMmenuinthebatchwindow,selectstatsthenselect:

fMRImodel

specification

Modelestimation

ContrastManager


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Directory:choosetheGLMdirectory

Unitsfor

designs:

scans

Interscaninterval:3.22

Click

Data

&

Design

then

New:

Subject/Session Scans:choosethefunctionalscans

Wewilladdtheconditionsusingmultiplecondition

and

regressor

files.

The

files

are

called: Multipleconditions:multi_condition.mat

Multipleregressors:multi_block_regressors.mat


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Tolookatthefile(notnecessaryfortheanalysis,butjustfordidacticpurposes)

>>load

multi_condition.mat

ThentypenamesoronsetsordurationintheMatlabcommandwindow.

Contains3cellarraysofthesamesize(notallentries

areshown

below)

names names{1}=Stationary; names{2}=Noattention;

onsets onsets{1} =[80170260350];

durations durations{1}=10;(canbejustasinglenumberifalleventshavethe

sameduration)


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Tolookatthefile(notnecessaryfortheanalysis,butjustfordidacticpurposes)

>>load

multi_block_regressor.mat

Thefilecontains avariableR.,whichisanNxMmatrix N=numberofscans M=numberofregressors

Blockregressors

model

different

sessions.

Use

this

command

to

set

up.

Canalsousevariouscombinationsofzerosandonesfunctions. >>R=kron(eye(3),ones(90,1));zeros(90,3)]); or >>R= [blkdiag(ones(90,1),ones(90,1),ones(90,1));zeros(90,3)];

1 2 3

50

100

150

200

250

300

350


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HighPassFilter:192

Note:

most

designs

will

use

a

high

pass

filter

value

of

128.

Thisdatasetrequiresalongerhighpass filterinordernot

tolosethelowfrequencycomponentsofthedesign.

Thedefaultvaluesontherestoftheentriesarecorrect

ClickModelEstimation SelectSPM.mat

Click

Dependency

and

choose

fMRI

model

specification:SPM.matFile


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Contrastmanager

SelectSPM.mat

ClickDependencyandchooseModelestimation:SPM.matfile

ContrastSessions

NewFContrast

Name:Effectsofinterest

Weightsmatrix:eye(3)

100

010

001


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ContrastSessions New

T

Contrast

Name:Attention

Weightsvector:[011]

NewT

Contrast

Name:Motion

Tcontrastvector:[211]

ClickSave

button

and

save

the

batch

file

ClickRunbutton(greenarrow)


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D.Gitelman

Thechange

in

the

designmatrix

comparedwiththe

previousslideisdue

tonon

sphericity

effects.


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D.Gitelman

ClickResults

SelectSPM.mat

ChooseAttentioncontrast

ApplyMasking:

None

pvalueadjust:None

Thresholdp:0.0001

&extentthreshold:10


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D.Gitelman

ClickResults

SelectSPM.mat

ChooseMotioncontrast

ApplyMasking:contrast

SelectMask:Attention

Uncorrectedmaskp:0.01

Natureofmask:inclusive

pvalueadjust:FWE

Thresholdp:0.05

&extentthreshold:3

Exampleofapsychologicalinteraction


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D.Gitelman

ResultsChooseSPM.mat Motioncontrast

ApplyMasking:none

pvalueadjustment:FWE

thresholdT

or

pvalue:

0.05

&extentthresholdvoxels:3

Gotopoint[15789]

Clickeigenvariate

Nameof

region:

V2

Adjustfor:EffectsofInterest

ROIdefinition:sphere

Sphereradius(mm):6

(TheVOIfileissavedtothe

GLMdirectory.)


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D.Gitelman

ClickPPI

button

SelectSPM.matintheGLMdirectory.

Analysistype:PPI

SelectVOI_V2_1.mat IncludeStationary:No IncludeNoAttention:

Yes

Contrastweight:

1

IncludeAttention:Yes Contrastweight:1 NameofPPI:V2x(Att

NoAtt)

(ThePPIfileisautomaticallysavedtotheGLMdirectory.


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D.Gitelman

Openbatchwindow

FromtheSPMmenuselectStats>Physio/Psychophysiologic

Interaction ForSPM.matselect

theoneintheGLM

folder

Typeof

analysis

:Psychophysiologic

Interaction


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D.Gitelman

Typeof

analysis

:Psycho

physiologicInteraction

VOI:choosetheV2VOI

Inputvariablesandcontrast

weights

Column1isthecondition(seeSPM.Sess.U),column2

willusuallybe1,column3isthecontrastweight.

Name

of

PPI:

:

V2x(Att

NoAtt)

Savethebatchfile

Runthebatchfile


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cdtotheGLMdirectory.

>>load

PPI_V2x(Att

NoAtt)

ThismustbedonebeforesettingupthePPIGLMsothevariablesareintheMatlabworkspace.

FromthetasksmenuatthetopoftheGraphicswindow

choose

Batch

Select

fMRImodelspecification

Modelestimation

ContrastManager


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Directory:choosethePPIV2directory

Unitsfor

design:

scans

(actually

doesnt

matter

in

thiscasesinceweuseonlyregressors).


AddaNew

subject/session

Scans:choosethefMRIscans

ClickRegressorsandadd3regressors

Regressor

1:

Name:

PPI

interaction,

Value:

PPI Regressor2:Name:V2BOLD,Value:Y

Regressor3:Name:Psych_AttNoAtt,Value:P

Cli k M l i l d h h


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ClickMultiple

regressors

and

choose

the

multi_block_regressor.matfile

HighPassFilter:192

ClickModel

Estimation

SelectSPM.matClickDependencyandchoosefMRImodelspecification:SPM.matFile

Contrastmanager

SelectSPM.mat

ClickDependencyandchooseModelestimation:SPM.matFile ContrastSessions NewTContrast

Name:

Interaction

V2

x

(Att

NoAtt) Weightsvector:[1]

Savethebatchfile Run


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PPI Y P


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D.

GitelmanD.

Gitelman

ClickResults

SelectSPM.mat

Choose PPIcontrast

ApplyMasking:None

Title:Interaction pvalueadjust:None Thresholdp:0.005(was0.01inspm8)

&extent

threshold:

3

GotoV5(39720)


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D.

GitelmanD.

Gitelman

Results Choose SPM mat


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D.

Gitelman

ResultsChooseSPM.mat

Motioncontrast

ApplyMasking:none

pvalueadjustment:FWE

thresholdT

or

pvalue:

0.05

&extentthresholdvoxels:3

Gotopoint[39720]

Clickeigenvariate

Nameof

region:

V5

Adjustfor:EffectsofInterest

ROIdefinition:sphere

Sphereradius(mm):6

(TheVOIfileissavedtothe

GLMdirectory.)

Click PPI button


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D.

Gitelman

ClickPPI

button

SelectSPM.matintheGLMdirectory.

Analysistype:PPI

SelectVOI_V5_1.mat IncludeStationary:No IncludeNoAttention:

Yes

Contrastweight:

1

IncludeAttention:Yes Contrastweight:1 NameofPPI:V5x(Att

NoAtt)

(ThePPIfileisautomaticallysavedtotheGLMdirectory.


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D.

GitelmanD.

Gitelman

cdtotheGLMdirectory

>>load

PPI_V5x(Att

NoAtt)

ThismustbedonebeforesettingupthePPIGLMsothevariablesareintheMatlabworkspace.

FromthetasksmenuatthetopoftheGraphicswindow

choose

Batch

Select

fMRImodelspecification

Modelestimation

ContrastManager


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Directory:choosethePPIV5directory

Unitsfor

design:

scans

(actually

doesnt

matter

in

thiscasesinceweuseonlyregressors).


Add

a

New

subject/session Scans:choosethefMRIscans

ClickRegressorsandadd3regressors

Regressor

1:

Name:

PPI

interaction,

Value:

PPI Regressor2:Name:V2BOLD,Value:Y

Regressor3:Name:Psych_AttNoAtt,Value:P

Click Multiple regressors and choose the


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ClickMultiple

regressors

and

choose

the

multi_block_regressor.matfile

HighPassFilter:192

ClickModel

Estimation

SelectSPM.matClickDependencyandchoosefMRImodelspecification:SPM.matFile

Contrastmanager

SelectSPM.mat

ClickDependencyandchooseModelestimation:SPM.matFile ContrastSessions NewTContrast

Name:

Interaction

(V5

x

(Att

NoAtt)) Weightsvector:[1]

Savethebatchfile

Run


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ClickResults

SelectSPM.mat

Choose

PPI

contrast ApplyMasking:None

Title:Interaction

pvalueadjust:None

Threshold

p:

0.001 &extentthreshold:10


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IfyouhaverunthroughboththeV2V5andthe

V5

V2sections

you

should

now

have

2VOI

files:

VOI_V2_1.matandVOI_V5_1.mat.

Ifyouhavenotrunthroughbothsectionsthen

goback

to

either

the

slides

titled:

Extracting

VOI:V2V5orExtractingVOI:V5V2andcreatetheVOIs


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Create4PPIs(ClickPPIbutton,thenchoosepsychophysiologicalinteractionasthetaskto

perform.) V2xNoAttention(UsetheV2VOIandincludeNoAttention

withacontrastweightof1,donotincludeStationary,Attention).Saveasv2noatt

V2xAttention(Use

the

V2

VOI

and

include

Attention

with

acontrastweightof1,donotincludeStationary,No

Attention).Saveasv2att V5xNoAttention(UsetheV5VOIandincludeNoAttention

withacontrastweightof1,donotincludeStationary,Attention).

Save

as

v5noatt

V5xAttention(UsetheV5VOIandincludeAttentionwithacontrastweightof1,donotincludeStationary,NoAttention. Saveasv5att


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LoadthePPIsyoujustcreated(TheywillbeintheGLMdirectory.)

>>v2noatt

=load('PPI_v2noatt.mat');

>>v2att=load('PPI_v2att.mat');

>>v5noatt=load('PPI_v5noatt.mat');

>>

v5att

=

load('PPI_v5att.mat'); PlotthePPIdatapoints

figure

plot(v2noatt.PPI.ppi,v5noatt.PPI.ppi,'k.')

holdon

plot(v2att.PPI.ppi,v5att.PPI.ppi,'r.');


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Draw

the

regression

lines >>lsline

Labelit

>>legend('NoAttention','Attention')

>>xlabel('V2eigenvariate')

>>ylabel('V5

eigenvariate')

>>title('Psychophysiologic Interaction')


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PPI Darren Gitelman

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Transcript of PPI Darren Gitelman